Research Article
Estimating Hospital Work Activities in Context-Aware Healthcare Applications
@INPROCEEDINGS{10.1109/PCTHEALTH.2006.361674, author={Jesus Favela and Monica Tentori and Luis A. Castro and V\^{\i}ctor M. Gonzalez and Elisa B. Moran and Ana I. Mart\^{\i}nez-Garc\^{\i}a}, title={Estimating Hospital Work Activities in Context-Aware Healthcare Applications}, proceedings={1st International ICST Conference on Pervasive Computing Technologies for Healthcare}, publisher={IEEE}, proceedings_a={PERVASIVEHEALTH}, year={2007}, month={5}, keywords={Activity estimation Context-aware computing Hospital activities Neural networks.}, doi={10.1109/PCTHEALTH.2006.361674} }- Jesus Favela
Monica Tentori
Luis A. Castro
Víctor M. Gonzalez
Elisa B. Moran
Ana I. Martínez-García
Year: 2007
Estimating Hospital Work Activities in Context-Aware Healthcare Applications
PERVASIVEHEALTH
IEEE
DOI: 10.1109/PCTHEALTH.2006.361674
Abstract
Hospitals are convenient settings for the deployment of context-aware applications. The Information needs of hospital workers are highly dependent on contextual variables, such as location, role and activity. While some of these parameters can be easily determined, others, such as activity are much more complex to estimate. This paper describes an approach to estimate the activity being performed by hospital workers. The approach is based on information gathered from a work study conducted in a hospital, in which 196 hours of detailed observation of hospital workers was recorded. This data is used to train a back propagation neural network to estimate user activity based on contextual variables such as location, artifacts being used, the presence of colleagues and the subjects' activity. The results indicate that the user activity can be estimated with 75% of accuracy (on average) which could be sufficient for some applications. We discuss how these results can be used in the design of activity-aware hospital information systems
